Clustering characteristics of gas-extraction induced seismicity in the Groningen gas field

Abstract

SUMMARY The Groningen gas field in the north of the Netherlands is one of the largest gas fields in the world. Since the early 1990s induced seismicity has been recorded. The largest magnitude event observed so far was a Mw = 3.6 event at the town of Huizinge in 2012. The risk posed by the induced events urged the necessity to build comprehensive seismological models capable of explaining the spatial-temporal distribution of the recorded seismicity and evaluating the regional seismic hazard and risk. The link between the occurrence of the seismicity and pressure depletion due to the production of the gas has been firmly established. However, the construction of comprehensive seismological models as well as hazard assessment is complicated by the fact that it is difficult to distinguish between induced and clustered events (events triggered by stress transfer of preceding, neighbouring events). This paper explores the contribution of clustered populations (i.e. aftershocks) to the Groningen induced seismic catalogue based on a statistical methodology in the time–space–magnitude domain. Specifically, the distributions of space–time distances between pairs of nearest-neighbour earthquakes, referred to as cluster style, is analysed. The cluster style of the Groningen induced seismicity is found to be very diffuse and characterized by a very low proportion of fore-/aftershock sequences and swarms (∼5 per cent) and a large proportion of repeater events (∼10 per cent). In contrast to human-induced seismicity in other regions, the background seismicity rate of Groningen is very low. Temporal variations in background seismicity rates can be related to changes in fault loading rates induced by gas production. Furthermore, a significant amount of independent, coincidental events (events occurring very close in time, but long distances apart) are observed. As the large gas field is fully connected, loading of the faults occurs roughly simultaneously throughout the field. Hence, the statistical probability of events occurring very close in time, but spatially far apart is significantly larger than in areas of fluid-injection induced seismicity The significant amount of repeaters and coincidental events cause an overabundance of events at intermediate time- and space-distances. This is further enhanced by the larger location errors in the catalogue increasing the estimated space-distance for non-relocated events. The diffusivity due to this overabundance of events at intermediate time- and space-distances, and the low-proportion of true fore-/aftershocks renders the statistical method used incapable of deriving a proper mode-separation value. However, this is not unique to this method. Any statistical method aimed at resolving two populations will break down if one of the populations analysed is too small. Hence, it is advisable to use caution when distinguishing fore-/aftershocks sequences or swarms for induced seismicity where the relative proportion of clustered events may be significantly lower than for tectonic events. In addition, given the small proportion of clustering and the general uncertainty in earthquake statistics, the results of this paper indicate that a distinction for earthquake risk modelling in Groningen is unnecessary.

Interevent-time distribution and aftershock frequency in non-stationary induced seismicity

“…Gas production in the Groningen field in the North of the Netherlands has resulted in induced seismicity with a rapidly increased non-stationary activity, amounting to a catalog of 397 events above the magnitude of completeness M = 1.3 in the period 1995-2018 ( Fig. 1a) [43][44][45][46][47][48][49][50][51] . The gas withdrawal causes reservoir compaction and associated stress build-up along pre-existing faults.…”

“…1d) causes the non-stationarity and hinders the use of the conventional statistical or probabilistic methods typically developed for stationary cases. There is no clear consensus on the importance of earthquake-earthquake interaction for Groningen's induced seismicity 44,47,49,50 . Uncorrelated human-induced triggers of seismic activity may, via earthquake-earthquake interaction, each entail internally correlated bursts of duration longer than the minimal time resolution.…”

Implications of the statistics of seismicity recorded within the Groningen gas field

“…Recently, there has been some interest in declustering the Groningen catalogue and estimate the number of correlated events using various techniques (Luginbuhl et al, 2018;Bourne et al, 2018;Candela et al, 2019;Muntendam-Bos, 2020;Post et al, 2021). We proposed a machine learning approach using the interevent time distribution as input to infer the proportion of aftershocks, the proportion of events following a Gamma distribution and the proportion of independent events.…”

“…An important question therefore is how many aftershocks are following Omori's power law, how many events a Gamma distribution and how many independent events an exponential distribution in the Groningen catalogue. Without explicitly distinguishing between aftershocks (Omori) and otherwise correlated events, the amount of correlated events was estimated to be between a few percent up to 27% (Luginbuhl et al, 2018;Bourne et al, 2018;Candela et al, 2019;Muntendam-Bos, 2020;Post et al, 2021). Most of the studies based on statistics assume stationarity to perform some form of declustering, except for the latter.…”

An overview of induced seismicity in the Netherlands

“…4b). Larger-magnitude events (M L ≥ 3.0) and surges of lower-magnitude events (0.5 ≤ M L ≤ 2.5) are still observed, though (Muntendam-Bos, 2020). This is due to the fact that stresses on the faults keep increasing with ongoing gas production although at a lower rate.…”